Energy Efficient Mobility in Wireless Sensor Network

International Journal Multimedia and Image Processing (IJMIP), Volume 1, Issues 3/4, September/December 2011

Vasaki Ponnusamy, Azween Abdullah Computer & Information Sciences Department Universiti Teknologi PETRONAS, Malaysia

Abstract A self-healing architecture is needed in order to allow sensor networks to heal from failures and Wireless sensors are used in many areas such as resume its service. Self-healing network must take environmental and habitat monitoring, indoor into consideration the severe resource limitation climate control, medical diagnostics, intelligent (energy) of sensor networks. [3] Looks into a new alarms, surveillance and many more. Since sensor concept of introducing mobile agent. It takes the nodes are placed in remote areas and require less processing load away from low powered sensors and attention and supervision, a significant number of uses hierarchical architecture. It is more energy these nodes require battery power to survive long efficient but does not look into having mobile agent periods of time. Recharging or replacing the battery as routing agent and reducing multi-hop operation. is often difficult since most of these units are placed SASHA [1] is a self-healing hybrid sensor network in areas which are difficult to access. Energy- using natural immune system concepts that uses constrained sensors deplete their energy quickly due automatic fault recognition and response. This to routing sensor data to the base station and also protocol only looks at faulty sensor readings and sensing the event. Energy depletion at these nodes does not look into approach of reducing energy causes routing hole and reduces network lifetime. conservation by means of self-healing. This paper introduces the method of exploiting One of the potential problems with current mobile nodes in the sensor network to increase routing protocols is that, it looks for lowest energy network lifetime and node lifetime. This mobile route and uses that route for every communication. nodes, known as mobile agents act as routing agents And this causes energy depletion along the path as to increase network lifetime as well as move in this is not good for network lifetime [3]. Moreover position searching for energy, recharge and deliver existing mechanisms rarely discuss on the cross- the harvested energy to static energy depleted nodes. cutting matters such as energy consumption, error- The mobile agent proposed in this paper travels checking etc [4]. Therefore an energy efficient between the static sensor nodes and base station in routing protocol is needed for the network to self- order to collect sensed data from the sensor nodes heal from energy depletion and routing failure. Self- and relay it to the base station. Moreover the mobile healing network must take into consideration the agent also performs energy harvesting to increase severe resource limitation (energy) of sensor node lifetime. The proposed architecture is inspired networks [1]. by plant biology (botany) based mechanism of the symbiosis interaction between plant root system and 2. Methodology microbes in the rhizosphere (soil) The many reasons for failure in sensor network such as energy exhaustion, malicious destruction and 1. Introduction malfunction [5] causes the destruction of coverage and connectivity. The failure also depends on the As sensor nodes are highly resource constrained, nature of application, its density, nodes closer to the energy efficient communication becomes one of the base station and environmental conditions. Some main issues to be dealt with. Energy-constrained nodes closer to the base station die faster as it sensors deplete their energy quickly due to routing forwards greater number of data to the base station. sensor data to the base station whilst sensing the All this effects on coverage and connectivity creates event. Most of the proposed solution [1][2] looks a coverage hole along the network. This is also into using static sensor nodes and multi-hop routing known as routing hole, whereby sensor nodes fail to convey sensed data. The use of multi-hop and causes a gap in the network where data cannot communication is a primitive WSN operation that is be forwarded. extremely fault-prone as well as energy-intensive. Therefore we propose a self-healing mechanism whereby the node failure due to energy depletion is

handled by proposing the use of mobile agent (MA). relationship with other micro-organism such as As stated by [6], one of the major advantages of microbe (mobile agent), fungi and bacteria. mobile wireless sensor network (WSN) over static The proposed architecture should look into WSN is its efficient energy utilization. The mobile consideration the following aspects: a middleware WSN proposed in this paper chooses an optimal node is responsible for communication between mobility pattern so that nodes closer to the sink are sensor nodes and base station, short range not utilized the most and this will prevent routing communication with base station to reduce the hole. The entire data aggregation and forwarding of distance ie. shortest path, avoid routing hole as much data to a base station is taken care by mobile nodes as possible, maintain fault-tolerance and hierarchical itself. [5] Proposes a new mechanism whereby in nature. Sensor networks discover their neighbor sensor nodes utilize the remaining energy by through a chemical messenger to create a relocating to combat the coverage holes. The nodes chemotactic relationship. Upon discovery, sensor are mobile by relocating to a location with coverage nodes create a cluster and elect a cluster head for holes, hence resulting in WSN healing. This communication purposes. As mentioned above, the approach relives the burden of sensor nodes from middleware proposed in this paper consists of mobile using multihop routing to relay data which would agents (microbe). The mobile agent creates a eventually cause sensor nodes failure near the base symbiosis relationship with sensor nodes to receive station as discussed. Moreover the mobile nodes do sensed data. Figure 1 shows how a mobile not need to visit every single node but to only obtain agent(middleware) helps in this context to convey data from the cluster head node. better targeting and data from the cluster head to the base station. These quality of communication is achieved. proposed MA helps in terms of short range As seen in figure 1, the proposed architecture communication thus avoids the routing hole issues. comprises of three layers. Layer 1 consists of all This is because the use of MA instead of cluster head static sensor nodes deployed, mobile agent sits at or sensor nodes for forwarding sensed data makes layers 2 and layer 3 consists of the base station. sure that sensor node do not deplete energy quickly. Mobile agents at layer 2 can be a laptop, mobile MAs are more powerful units which can have higher phone, mobile sensor on airplane, robot etc battery lifetime. depending on the nature of the setup. The proposed Mechanisms that save energy should be identified architecture is inspired by plant biology-based in order to extend the life of the network. Energy (botany) communication. The plant biology harvesting is another issue that has to be taken into communication in this context mainly looks at the consideration in order to extend the life of the mass communication that takes place at plant network [7]. There have been many researches going rhizosphere (sensor area), an information on in environmental power scavenging techniques [8] superhighway underground. and [9] also work on energy replenishment with the use of mobile robots in sensor network. [10] Proposes BS Layer 3 a method by having mobile robots as energy producers. These nodes recharge themselves by

Layer 2 moving to locations with abundant energy supply. Once they have enough energy, they migrate to areas in the network for delivering energy to the static sensor nodes. In this method a small percentage of network nodes are mobile by allowing them to move to search for energy, recharge, and deliver energy to immobile, energy-depleted nodes. This approach is Layer 1 known as energy harvesting or energy scavenging.

Figure 1. Mobile agent based architecture in 3. Nature Inspired Framework WSN The biological system can be mapped well to communication system and more applicably to the The plant (sensor) using its root system focus of this paper on self-healing characteristics. communicates with other plant root systems in the The mechanisms in this context include balance on rhizospehere. The entire three-tier architecture is the internal equilibrium (homeostasis) and on the inspired by the nature of how plant root system self-organization mechanism to support discover their neighbors, form a colony, create a environmental changes. During the lifespan of the defense mechanism against other plants or intruder WSN communication system, various changes occur which is known as allelopathy and symbiosis such as energy depletion, shortening lifespan, external threat or route diversion. Based on these

changes, the system should be able to self-learn, self- applicable to sensor network where sensor nodes are organize and self-heal from such events. These self- always sensitive to any possible threats or changes in management activities are similar to living the environment that is being sensed. Sensor organisms such as human, animals and plants networks can be programmed to form a cluster with whereby they learn and reform (self-heal) [11]. homogenous nodes and avoid any possibilities of The plant based biologically inspired mechanism overcrowding of sensor within the same proximity of consists of three layers as is proposed in figure 1 for area. sensor network. i) layer 1 consists of plants with its root mechanism and coordination with the U(Si) deployed with node position Sxyz rhizoshere, ii) layer2 consists of the communication while(sensor_status=‘IDLE’ or ‘ACTIVE’) of the plant with the microbe organisms in the rhizosphere and iii) layer 3 consists of generate Etd and tcluster communication of the microbe organisms with the (While tcluster != 0) base station. This architecture is well mapped to the Sensor Si broadcast “MHELLO” Si(Sid sensor network in which the plant system is ,Sxyz,CE(Si)) to U(Si) associated with sensor nodes and microbe organism Sensor Sj receives message from its neighbour is associated with the mobile agent. Sj generate MListA (Sj) = {(S1,Sxyz,CE(S1)), (S2,Sxyz,CE(S2)),…..(SnSxyz,CE(Sn))} As can be seen in figure 2, the operation of plant biology as in this context mainly happens at the plant rhizosphere which is the soil mechanism. The plant *Where MHELLO = organic acid (for neighbor discovery) leaf (sensor node) is exposed to sensing environment to continuously seek for the event. The sensing The chemical secretion into the rhizosphere environment is associated with sun light and its creates a chemotactic relationship between natural resources. Plant uses light from the sun to do organisms in the soil area which can be a positive or something beyond what science can think of: it takes negative reaction. The positive reaction is called the molecules of carbon dioxide and water and symbiotic relation such as the association of microbe compounds them together to make carbohydrates. Plant leaves get sunlight to produce carbon ion (sensed data) through photosynthesis process. The carbon ions from the leaf then are transported to other parts of the plant and mainly to the root system.

3.1. Defense Mechanism

Plants also have the capability of continuously communicating with the surrounding root systems of neighboring plants and can respond quickly to any invading roots of other species plants through chemical messengers. This allelopathic communication is triggered through pythotoxins secreted by plant roots in order to maintain a terrestrial plant community. This mechanism can be applied to sensor network where sensor nodes communicate with others and avoid the intrusion of any threats or possible attacks. This is one of the

3.2. Neighbor Discovery

The root system in the rhizhosphere detects each other through a neighbor discovery process as similar to sensor network in which sensor nodes detects each other through a neighbor discovery process. Moreover, plants have the capability of detecting plants of their same colony and form a cluster of community. They can send messages to one another of any possibilities of surrounding attacks, or threats by other animals from other colony. The plant root Figure 2. Plant Biology Inspired Framework for system is also very sensitive to overcrowding by the WSN same or other species. The same concept is

or fungi and nitrogen-fixing bacteria. These reactions Else if (CE(CH(Si)) < Etd are through organic acid and amino acids { (communication messages) secreted by plant roots. MAi send MENERGY to CH(Si) The negative reaction includes interactions with CH(Si) send MFINISH to MAi } parasitic plants and insects [12]. The positive communication is associated with communication Migration among sensor nodes and mobile agents visiting the sensor area to collect sensed data. The sensor nodes Microbes are always mobile as in when there is and mobile agents communicate through messages scarce supply of food or nutrient from current (amino acid) exchanged between them. symbiotic plant, it moves to other neighboring plants to acquire it. This natural selection mechanism Symbiosis Communication happens to mobile agents whereby it moves from cluster to cluster in order to collect sensed data. Once The next layer of communication is the symbiosis enough information is received, mobile agent then relationship between plants (sensor nodes) and would move to the base station in order to forward to microbe (mobile agent) living in the soil rhizosphere. the base station. This symbiotic relationship is a two way dependency where plants depend on microbe to process water in MAi migrate to other cluster the soil and recycle them back into foodstuffs for status_MAi = ‘ROAMING’ plant growth and vice versa whereby microbe depends on the plant by root exudates as a main 4. Protocol Overview component of food. The interchange of compounds between these two organisms provides a mechanism The following section discusses the operation of of warning signals [12]. These associations can be the protocol in detail by using the ideas of mobile seen in a communication between sensor nodes and agent and the three-tier architecture. mobile agents where a sensor node typically sends sensed data to the mobile agent and the mobile agent 4.1 . Layer1: sensor node to sensor node depends on the sensor node to collect and forward communication: cluster formation data.

This is the first phase where sensor nodes perform If(status_MAi =‘ROAMING’||status_MAi = ‘URGENT’ a neighborhood discovery in order to detect the MA detect cluster by random walk path presence of one another. The neighborhood through GPS discovery process is important so that sensor nodes MAi broadcast “MHELLO” MAi(MAid ,MAxyz)to could take part in the formation of cluster. And this U(Si) process helps in the election of cluster head (CH) for CH(Si) inspect B_CH(Si) a particular cluster. Also nodes discover their if (B_CH(Si) != empty) neighbor for future reference, if there incurs any Status_CH = ‘COMM’ possible threats and to prepare for a defense CH(S ) generate MList i C mechanism amongst sensor nodes. Sensors within CH(Sj) = {( MAid ,MAxyz)} inter and intra cluster can communicate with each CH(Si) send “MAGGR” T CH(S S )) to MA other to form any future security and defense id j, xyz i mechanisms. The following is how the protocol and Bag_MAi = MAGGR the algorithm are devised: MAi send MACK to CH(Si) CH(Si) flush buffer i. S  S: Upon start, sensor nodes starts a timer CH(Si) send MFINISH to MAi and send a hello message to each other notifying its presence.(message type=000). Hello message is sent *Where MHELLO and MFINISH = organic acid (for neighbor to all sensors within a hop distance of h (cluster), the discovery) value h is determined based on signal strength. All sensor nodes start with the same amount of energy. This idea also inspires the concept of energy The hello message consists of sensor node harvesting and scavenging whereby mobile sensors identification, GPS location of sensor node and (microbe) can recharge energy at sensor nodes remaining energy level. (plant). The energy harvested by mobile agent can be transferred to the sensor nodes. Mobile agent helps - Upon receiving hello message, all sensor nodes sensor nodes to preserve the battery resource by create a member list of nodes attached within hop acting as a middleware to forward sensor data to the distance h. All the fileds in the hello message is base station. Sensor nodes self-heal from energy copied into the membership list. depletion and this increase the network lifetime. The membership list appears as such:

{(1,X1Y1,E1),(2,X2Y2,E2),(3,X3Y3,E3)} - 1 refers to MA learns to visit only clusters within nearer node identification, XY refers to GPS position and E proximity. This is possible by all MA maintaining a refers to the remaining energy level. path visit list. ii. S: Sensor nodes inspect its member table to i. MA  CH: When mobile agent detects the decide which node has the highest amount of energy presence of sensor nodes (based on GPS location), it compared to the threshold value to be the cluster sends a hello message consisting of GPS location head. If other nodes within the member table have and mobile agent ID to the sensor nodes. higher energy than threshold, then do nothing. Else ii. CH  MA : Upon receiving this message, only if it has the highest energy level, then elect self to be the current cluster head will respond to mobile the cluster head (CH). agent. Before communicating, cluster head inspects iii. CH  S : CH broadcasts Sink-up message its data bag to decide whether there is any data to be (message type = 001) to other sensors within hop sent. If the bag is empty, then CH will not respond to distance h to announce its decision to be the cluster MA. Otherwise CH responds to MA by sending head. message that consists of CH ID, cluster member list iv. S  CH : Sensor nodes decide which cluster it and the complete aggregated data from the data bag. wishes to join and send back a join message(message CH keeps MA node identification in member list for type = 010) to CH. v. CH: CH updates its member list of all nodes future communication. belongs to cluster and creates a schedule for all iii. MA : MA stores membership list as path visited sensor nodes above the threshold value to send data {CH = 5,(1,X1Y1,E1),(2,X2Y2,E2),(3,X3Y3,E3)} based on the schedule created. All other sensor iv. CH: After sending the data, CH will flush the nodes below the threshold value goes into sleep buffer (data bag) to empty the old data and create mode. The structure of CH member list is: space for new data from sensors. {CH = 5,(1,X1Y1,E1),(2,X2Y2,E2),(3,X3Y3,E3)} v. Upon inspecting the energy level of nodes in the whereby the CH_ID is 5 and the remaining list is the membership list, MA decides nodes that need to be same as sensor member list created earlier. recharged. In this case MA moves to the closer proximity of this node and perform recharging. vi. S  CH : Sensor node senses event and sends vi. MA : MA waits for a random period of time and if data to the CH based on the schedule created. no more data being received, MA then decides to vii. CH : CH creates a buffer to store all the messages being received from sensor nodes. Data move to other clusters which enables MA to aggregation is performed at this point whereby CH piggyback data from. Before leaving the cluster, MA filters redundant data and also compares data from informs CH about its migration. This is to ensure all sensors to have a complete collection of data. that CH does not send anymore data to this MA. When sensor timer reaches a determined value, vii. CH : Upon receiving the migration information, step i. starts all over again by all sensor nodes, CH removes MA identity from its member list and within hop distance h (including sensor in sleep looks for other MA that comes within the range of mode) sending a hello packet to each other. communication. Note : For the sink message and join message, the viii. MA : MA moves to other clusters to piggyback GPS position and remaining energy is set to nil since more data and the same process from i. to vii. is sensors have already obtained these information applied in this context. from the hello message and already in the member MA : once the data bag of MA is full, MA decides to list. This will save overhead of the message deliver the message to base station, and moves towards the base station 4.2 . Layer 2: sensor node to mobile agent communication 5. Energy Analysis of various mechanism This is the layer 2 communication whereby mobile agent communicates with the sensor node. Researchers are looking into possibility of Mobile agents are always in the moving position and shortening transmission distance using various its location information is continuously tracked using methods such as i. shorter routing path using GPS. Mobile agents have the capability of detecting multihop routing ii. using cluster head [13], iii. using GPS position of sensor nodes within the mobile relay or agent [14], iv. using message neighborhood and the reverse is true whereby when a ferrying approach and v. mobile sink to reduce the mobile agent comes into contact with the cluster, the distance. The mathematical analysis presented in this cluster head is able to detect the presence of mobile paper, looks at 5 different approaches looking into agent. For the initial round, the order of cluster visits total energy consumption pattern for energy by MA takes place in random fashion after which consumption using i. multihop routing, ii. cluster

head, iii, direct transmission, iv. mobile agent with Energy consumption using direct transmission cluster head, and v. mobile agent with direct transmission(refer to figure 3). We are analyzing the Total Energy Consumption = Energy Energy energy patterns looking into the energy consumed at trans + sense nodes located nearer to the base station. These nodes 2 = µ X d X a + Ə X a + Ĉ X a assumed to be consuming more energy since it has to 2 forward data that comes from other nodes from other = a (µ X d + Ə + Ĉ) (3) parts of the network as well (for multihop communication). Since the base station is assumed to Energy consumption using mobile with cluster head be located at the centre of the network, more traffic is concentrated there. The analysis presented will prove that mobile agent based routing mechanism = ( 2πL r2 ) Ə X a+ (πL r2) µ X H 2 X a could be a potential solution for energy efficient N2 N2 2 2 2 operation. = a (2πL r ) Ə + (πL r ) µ p X H ) (4)

N2 N2

where H < r

Mobile with direct transmission Energy consumption using mobile with direct transmission Mobile with Multihop cluster head Total energy Total Energy Consumption = Energytrans + Energysense consumptio 2 = µ X H X a + Ə X a + Ĉ X a where H < r

Direct Cluster head 2 2 = a L (µ X H + Ə + ) (5) transmission Ĉ π r2

Figure 3. Category of energy consumption The following section discusses some of the analysis outcome or results obtained from simulation performed by other researchers by comparing with This energy model is extracted from [17,18] and the mathematical analysis presented here. The results LEACH [13] also considers similar model for its first obtained are from various approaches such as order radio model. The load in the network is clustering concept, use of mobile agent, biological calculated based on the analysis performed by [19 ]. inspired concepts and direct transmission. These results will help in future simulation of the protocol mentioned in section 4. The results obtained by using mobile agent to cover routing hole and energy Assume Ĉ = Energycpu Ə = Energyelec µ= Energyamp harvesting should produce better results compared to the results shown by other approaches. Energy consumption using multihop

1 2 2 2 Direct = ( L - 1 ) Ə X a + (L ) Ə + µ X d X a + Ĉ X a 2 2 Dissipated π r π r 0.5 MTE

System(J) 2 2 2 2 LEACH Energy = a ( L ) Ə - Ə (L ) Ə + (L ) µ X d + Ĉ 0 π r2 π r2 π r2 Total 20 60 0 2 2 2 100 140 18 = a ( 2L ) Ə + (L ) µ X d + Ĉ (1)

π r2 π r2 Network Diameter(M)

Figure 4. Total System Energy Dissipated Energy consumption using cluster head Figure 4 shows the total system energy dissipated by comparing LEACH [13] with two other protocols 2 2 2 = a (2πL r ) Ə + (πL r ) µ X d + Ĉ namely direct communication with the base station and minimum-energy multi-hop routing (MTE). 2 ͌͌ a (µ X d + 2 Ə + Ĉ ) (2) Using a direct communication protocol by referring to Eq.3, each sensor sends its data directly to the

base station. If the base station is far away from the energy consumption from the highest to the lowest nodes, this communication require high transmit is: Direct –> MTE/Flat (multihop) -> LEACH power from each node as total energy consumption is (cluster) -> SENMA/proposal (mobile) (figure 7). proportional to d2, the transmission distance. In MTE, nodes route data destined for the base station Direct multihop cluster mobile through intermediate nodes (as referred to Eq.1). LEACH is a clustering based approach which shows better performance compared to two other Figure 7. Flow of energy consumption approaches (Eq.2). It is proven that mobile agent consumes the least energy for routing sensor data to the base station.

8000 And direct communication consumes the most 6000 energy for communicating sensor data to the base SENMA

energy 4000 FlatAdHoc station. Direct transmission may not be a viable 2000 solution to reduce energy consumption in sensor Total 0 consumption(J) networks. As seen in Eq.3, energy consumption will 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 be affected by the transmission distance and energy Density of deployment consumption of nodes further away from the base station is four times more than nodes closer. These Figure 5. Total Energy Consumption increases linearly as the radius increases and the energy consumption will be proportional to d4 after

the threshold value of transmission distance. Using a Figure 5 shows the total energy consumption cluster head approach, sensors are only responsible over density of network for two different protocols, for sensing the event and relaying data to the cluster namely flatAdHoc network and SENMA [14]. head. Tremendous energy is saved as sensor nodes SENMA deploys mobile agents(Eq.5&6) for do not take part in routing and transmission of data communication with the base station in which mobile as energy consumption is directly proportional to agents are powerful hardware units which can be an transmission distance. But as cluster head selection is aerial vehicle or ground vehicle. In this architecture, on a rotational basis, sensor nodes would eventually mobile agents are responsible to convey sensor data deplete energy when it becomes the cluster head as it to the base station. Whereas in flatAdHoc has to receive and send data from other nodes. architecture (Eq.1), sensor nodes are continuously Moreover based on Eq. 2 energy consumption using consuming energy in order to route data from clustering approach is also affected by the width of neighbor nodes. As seen in the figure 5, the the network since cluster head has to communicate deployment of mobile agent consumes lesser energy using longer distance. Multihop communication compared to flat architecture using multihop routing. ensures delivery of data as the data is forwarded by This can be useful results to benchmark with the intermediate nodes. But multihop approach causes architecture proposed in this paper deploying mobile routing holes as nodes closer to the base station are agent for routing as well as energy harvesting. heavily utilized and deplete energy quickly. The

0.8 mobile agent based approach should be able to overcome the problem encountered by multihop as 0.6 LEACH 2 Power 0.4 MONSOON energy consumption in multihop is dependent ( 2L ) 2 0.2 Proposal whereas in mobile approach it is dependent on ( L ). Average Consumption(mJ) 0 The discussion in the following section proves that 2 4 6 8 10 12 14 16 18 20 energy consumption using mobile approach is two Number of Rounds times lesser than multihop routing.

Figure 6. Average Power Consumption 6. Energy consumption and lifetime of Figure 6 shows average power consumption for mobile approach three different protocols in which LEACH is a clustering based (Eq.3) approach, MONSOON [15] Theorem 1 : Total energy consumption using mobile is a biologically inspired framework that consists of agent is lower bounded by 1/ 2ec , where ec is energy agents and middleware platform. The proposed consumed by multihop routing framework (proposal)(Eq 5&6) implements sensing data collection applications with each node Proof:Assume Ĉ = Energycpu Ə = Energyelec µ= deploying a Sensing Agent (SA) with a randomly- Energyamp generated behaviour policy. Based on the results 2 2 presented with the mathematical analysis and energy consumed by mobile em= aL (µ X H + Ĉ ) comparison with other research works, the order of π r2 2 2 energy using multihop eC = 2aL (µ X d + Ə+ Ĉ )

π r2

Looking at eC and em , eC > em or em < 1/2 eC since H < d and eC = ½ em whereby eC is depending on distance H and em depending on distance d, Therefore, em < ½ ec (energy mobile is lower bounded by ½ energy multihop)

Figure 9. Energy consumption per node for different distance

7. Case Study: Illegal Immigration Detection

The mobile agent based approach discussed above will be applied into a prototype development into the illegal immigration detection system to prove with more applicable results. In line with the concern on protecting the country against illegal immigration Figure 8: Energy consumption per node and threat, a new mechanism using mobile wireless sensor technology is proposed. It is a self-healing Figure 8 outlines the results obtained from wireless sensor network to detect any illegal experiment using real sensors with each sensor immigrant moving into the country via forest or boards attached to the standard battery. The energy borders. This is specifically applicable immigrants consumption per node is traced by deploying the entering the country through forest borders. I t is network in a multihop mechanism. The results predicted that most of the refugees and immigrants obtained shows that mlutihop communication from Myanmar are entering the country through consumes more power and the energy in terms of Malaysia-Thailand border. The sensor technology voltage drops significantly as compared to direct proposed is intelligent enough to detect any communication. In this case the direct movements by using image processing techniques communication is configured as mobile architecture. such as motion sensors, vision sensors and sound Whereas figure 9 energy consumption for nodes sensors to further analyze the profile. placed near the mobile agent as well as nodes further away from the mobile agent. This shows that distance between mobile and sensor node is crucial for energy analysis.

Theorem 2: The lifetime of a node inversely proportional to distance H (between sensor node and mobile agent) and network width.

Proof initial energy of a node = E energy per node using mobile agent = eC

Therefore the lifetime of a node = E/ eC And assuming 2 2 eC = aL (µ X H + Ə) + Ĉ Figure 10. Illegal immigration system using π r2 mobile sensors 2 2 and lifetime per node = E / aL (µ X H + Ə + )+Ĉ π r2 This is considered as micro-level technology = π r2 ( E ) that can detect any events in a smaller scale using 2 2 image processing techniques as compared to remote aL (µ X H + Ə + ) Ĉ sensing technology which is unable to detect events hidden from the satellite view. This technology works by static sensors being deployed to

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